A note on the prediction error of principal component regression

Understand

We analyse the prediction error of principal component regression (PCR) and prove non-asymptotic upper bounds for the corresponding squared risk.

• Under mild assumptions, we show that PCR performs as well as the oracle method obtained by replacing empirical principal components by their population counterparts.
• Our approach relies on upper bounds for the excess risk of principal component analysis.